论文信息 - Wavelet ANN based transformer fault diagnosis using gas-in-oil analysis

Wavelet ANN based transformer fault diagnosis using gas-in-oil analysis

This paper describes a wavelet artificial neural network (ANN) for signal classification, and applies it for transformer Fault Detection with dissolved gas analysis (DGA). The weights of the network are replaced by wavelet functions and are corrected by conjugate gradient method in the training iteration. Preliminary simulation results show wavelet ANN for DGA can get a 95% correct diagnosis rate, superior then BP ANN. Besides, precondition techniques of input data is studied, a suitable precondition algorithm play an important role in ANN.

Li Honglei | Xiao Dengming | Chen Yazhu

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